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How to Keep Up with Your Quants

In this era of big data, analytics are becoming a competitive necessity, and companies of all industries need general managers who can work effectively with “quants” to ensure that their work yields more effective decisions, according to Thomas H. Davenport, President’s Distinguished Professor of Information Technology and Management at Babson College, and author of Keep Up with Your Quants, in the July/August issue of Harvard Business Review.

For people fluent in analytics, that should be no problem, notes Professor Davenport, a senior adviser to Deloitte Analytics and the director of research at the International Institute for Analytics. For those who aren’t, he says it’s time to start thinking differently and offers a primer for non-quants on how to work with quants and use analytics to produce better strategic and tactical decisions. Following are highlights from his recent article:

Start by thinking of yourself as a consumer of analytics: The producers are the quants whose analyses and models you’ll integrate with your business experience and intuition as you make decisions. Your job as a data consumer—to generate hypotheses and determine whether results and recommendations make sense in a changing business environment—is critically important.

Learn a little about analytics: If you remember the content of your college-level statistics course, you may be fine. If not, bone up on the basics of regression analysis, statistical inference and experimental design. When using big data to make big decisions, non-quants should focus on the first and the last steps of the process. The numbers people typically handle the details in the middle, but wise non-quants ask lots of questions along the way. To become more data literate, enroll in an executive education program in statistics, take an online course, or learn from the quants in your organization by working closely with them on one or more projects.

Align yourself with the right kind of quant: Quants and the consumers of their data get much better results if they form deep, trusting ties that allow them to exchange information and ideas freely. Of course, highly analytical people are not always known for their social skills, so this can be hard work.

Focus on the beginning and the end: Framing a problem—identifying it and understanding how others might have solved it in the past—is the most important stage of the analytical process for a consumer of big data. It’s where business experience and intuition matter most.

Establish a culture of inquiry, not advocacy: Most everyone is familiar with the adage: “Figures lie and liars figure.” Analytics consumers should never pressure their producers with comments like “See if you can find some evidence in the data to support my idea.” Instead, the explicit goal should be to find the truth.

Ask lots of questions along the way: No matter how much an executive may trust their quants, they shouldn’t stop asking them tough questions. Frank Friedman, chief financial officer and managing partner for finance and administration of Deloitte’s U.S. business, is an inveterate questioner. He has assembled a group of data scientists and quantitative analysts to help him with several initiatives, including optimizing the pricing of services, developing models that predict employee performance, and identifying factors that drive receivables. “People who work with me know I question a lot—everything—always,” Friedman says. “After the questioning, they know they will have to go back and redo some of their analyses.” He also believes it’s vital to admit when you don’t understand something: “I know I am not the smartest person in the room in my meetings with these people. I’m always pushing for greater clarity [because] if I can’t articulate it, I can’t defend it to others.”

Published with permission from Harvard Business Review Press. Professor Davenport also is a coauthor of the book, Keeping Up with the Quants (Harvard Business Review Press, 2013) and is author of the forthcoming bookBig Data at Work, from Harvard Business Review Press.

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